Systems and methods for controlling imaging

ABSTRACT

A method for controlling a medical device may be provided. The method may include obtaining, via one or more cameras, first data regarding a first motion of a subject in an examination space of the medical device. The method may include obtaining, via one or more radars, second data regarding a second motion of the subject. The method may further include generating, based on the first data and the second data, a control signal for controlling the medical device to scan at least a part of the subject.

CROSS-REFERENCE OF RELATED APPLICATION

This application a continuation of U.S. patent application Ser. No.16/455,869, filed on Jun. 28, 2019, which claims priority of ChinesePatent Application No. 201910378793.3, filed on May 8, 2019, thecontents of which are hereby incorporated by reference.

TECHNICAL FIELD

The present disclosure generally relates to a medical device, and moreparticularly, relates to systems and methods for controlling imaging ofthe medical device.

BACKGROUND

Imaging is widely used in a variety of medical treatments and/ordiagnostics. Various imaging devices (e.g., a computed tomography (CT)device, a magnetic resonance imaging (MRI) device, or a positronemission tomography (PET) device) can be used to perform imaging byscanning a subject (e.g., a patient). A motion of the subject during thescan, such as a cardiac motion or a respiratory motion, may cause motionartifacts. For example, during an MRI scan, if the patient moves his orher head, a final reconstructed image may include motion artifactsand/or become blurry. In this case, a diagnosis and treatment of adisease on the basis of the reconstructed image including the motionartifacts may be unrealiable due to a poor image quality. Therefore, itis desirable to develop systems or methods to control an imaging devicein order to reduce or avoid motion artifacts in imaging.

SUMMARY

According to a first aspect of the present disclosure, a method forcontrolling a medical device is provided. The method may include mayinclude one or more operations. The one or more operations may beimplemented by at least one processing device. The at least oneprocessing device may obtain, via one or more cameras, first dataregarding a first motion of a subject in an examination space of themedical device. The at least one processing device may obtain, via oneor more radars, second data regarding a second motion of the subject.The at least one processing device may generate, based on the first dataand the second data, a control signal for controlling the medical deviceto scan at least a part of the subject.

In some embodiments, the at least one processing device may obtain scandata acquired by the medical device, and reconstruct a medical imagebased on the scan data.

In some embodiments, the at least one processing device may acquire, viathe one or more cameras, a plurality of image frames regarding the firstmotion of the subject. The at least one processing device may determine,based on at least a part of the plurality of image frames, the firstdata including one or more motion parameters of the first motion.

In some embodiments, the one or more motion parameters of the firstmotion may include one or more translation matrices and one or morerotation matrices.

In some embodiments, the at least one processing device may acquire, viathe one or more radars, radar echo data from the subject. The at leastone processing device may correct the radar echo data according to theone or more motion parameters of the first motion, and extract, from thecorrected radar echo data, the second data including cardiac motion dataor respiratory motion data.

In some embodiments, the plurality of image frames and the radar echodata may be acquired simultaneously by the one or more cameras and theone or more radars, respectively.

In some embodiments, the at least one processing device may generate,based at least in part on the second data, the control signal using agating technique.

In some embodiments, the first motion may include a rigid motion of thesubject, and the second motion may include a physiological motion of thesubject.

In some embodiments, the medical device may include at least one of acomputed tomography (CT) device, a magnetic resonance imaging (MRI)device, a positron emission tomography (PET) device, or a radiationtherapy (RT) device.

According to a second aspect of the present disclosure, a system forcontrolling a medical device may be provided. The system may include atleast one storage device including a set of instructions, and at leastone processor in communication with the at least one storage device.When executing the set of instructions, the at least one processor mayobtain, via one or more cameras, first data regarding a first motion ofa subject in an examination space of the medical device. The at leastone processor may obtain, via one or more radars, second data regardinga second motion of the subject. The at least one processor may generate,based on the first data and the second data, a control signal forcontrolling the medical device to scan at least a part of the subject.

According to a third aspect of the present disclosure, a medical systemmay be provided. The medical system may include a medical device, one ormore cameras, one or more radars, at least one storage device includinga set of instructions, and at least one processor in communication withthe at least one storage device. The one or more cameras may beconfigured to acquire a plurality of image frames of a subject in anexamination space of the medical device. The one or more radars may beconfigured to acquire radar echo data from the subject. When executingthe set of instructions stored in at least one storage device, the atleast one processor is directed to cause the medical system todetermine, based on the plurality of image frames, first data regardinga first motion of the subject. The at least one processor is directed tocause the medical system to determine, based on the radar echo data,second data regarding a second motion of the subject. The at least oneprocessor is directed to cause the medical system to generate, based onthe first data and the second data, a control signal for controlling themedical device to scan at least a part of the subject.

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities, andcombinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. These embodiments are non-limiting exemplaryembodiments, in which like reference numerals represent similarstructures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary medical systemaccording to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating an exemplary medical deviceaccording to some embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating an exemplary work schemeaccording to some embodiments of the present disclosure;

FIG. 4 is a schematic diagram illustrating an exemplary data acquisitionaccording to some embodiments of the present disclosure;

FIG. 5 is a block diagram illustrating an exemplary medical imagingsystem according to some embodiments of the present disclosure;

FIG. 6 is a block diagram illustrating an exemplary processing deviceaccording to some embodiments of the present disclosure;

FIG. 7A is a flowchart illustrating an exemplary process for controllinga medical device according to some embodiments of the presentdisclosure;

FIG. 7B is a schematic diagram illustrating an exemplary cardiac gatingaccording to some embodiments of the present disclosure;

FIG. 7C is a schematic diagram illustrating an exemplary respiratorygating according to some embodiments of the present disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for extractingphysiological motion related data according to some embodiments of thepresent disclosure;

FIG. 9 is a schematic diagram illustrating an exemplary systemcalibrating according to some embodiments of the present disclosure;

FIG. 10 is a schematic diagram illustrating an exemplary respiratorysignal according to some embodiments of the present disclosure;

FIG. 11 is a schematic diagram illustrating an exemplary ECG signalaccording to some embodiments of the present disclosure; and

FIG. 12 is a flowchart illustrating an exemplary process for generatingan image according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant disclosure. However, it should be apparent to those skilledin the art that the present disclosure may be practiced without suchdetails. In other instances, well-known methods, procedures, systems,components, and/or circuitry have been described at a relativelyhigh-level, without detail, in order to avoid unnecessarily obscuringaspects of the present disclosure. Various modifications to thedisclosed embodiments will be readily apparent to those skilled in theart, and the general principles defined herein may be applied to otherembodiments and applications without departing from the spirit and scopeof the present disclosure. Thus, the present disclosure is not limitedto the embodiments shown, but to be accorded the widest scope consistentwith the claims.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise,”“comprises,” and/or “comprising,” “include,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

It will be understood that the term “system,” “engine,” “unit,”“module,” and/or “block” used herein are one method to distinguishdifferent components, elements, parts, section or assembly of differentlevel in ascending order. However, the terms may be displaced by anotherexpression if they achieve the same purpose.

Generally, the word “module,” “unit,” or “block,” as used herein, refersto logic embodied in hardware or firmware, or to a collection ofsoftware instructions. A module, a unit, or a block described herein maybe implemented as software and/or hardware and may be stored in any typeof non-transitory computer-readable medium or other storage device. Insome embodiments, a software module/unit/block may be compiled andlinked into an executable program. It will be appreciated that softwaremodules can be callable from other modules/units/blocks or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Software modules/units/blocks configured for execution oncomputing devices (e.g., processing device 240 as illustrated in FIG. 2) may be provided on a computer-readable medium, such as a compact disc,a digital video disc, a flash drive, a magnetic disc, or any othertangible medium, or as a digital download (and can be originally storedin a compressed or installable format that needs installation,decompression, or decryption prior to execution). Such software code maybe stored, partially or fully, on a storage device of the executingcomputing device, for execution by the computing device. Softwareinstructions may be embedded in a firmware, such as an EPROM. It will befurther appreciated that hardware modules/units/blocks may be includedin connected logic components, such as gates and flip-flops, and/or canbe included of programmable units, such as programmable gate arrays orprocessors. The modules/units/blocks or computing device functionalitydescribed herein may be implemented as software modules/units/blocks,but may be represented in hardware or firmware. In general, themodules/units/blocks described herein refer to logicalmodules/units/blocks that may be combined with othermodules/units/blocks or divided into sub-modules/sub-units/sub-blocksdespite their physical organization or storage. The description may beapplicable to a system, an engine, or a portion thereof.

It will be understood that when a unit, engine, module or block isreferred to as being “on,” “connected to,” or “coupled to,” anotherunit, engine, module, or block, it may be directly on, connected orcoupled to, or communicate with the other unit, engine, module, orblock, or an intervening unit, engine, module, or block may be present,unless the context clearly indicates otherwise. As used herein, the term“and/or” includes any and all combinations of one or more of theassociated listed items.

These and other features, and characteristics of the present disclosure,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, may become more apparent upon consideration of thefollowing description with reference to the accompanying drawings, allof which form a part of this disclosure. It is to be expresslyunderstood, however, that the drawings are for the purpose ofillustration and description only and are not intended to limit thescope of the present disclosure. It is understood that the drawings arenot to scale.

For illustration purposes, the following description is provided to helpbetter understanding an imaging process. It is understood that this isnot intended to limit the scope of the present disclosure. For personshaving ordinary skills in the art, a certain amount of variations,changes and/or modifications may be deducted under the guidance of thepresent disclosure. Those variations, changes and/or modifications donot depart from the scope of the present disclosure.

Provided herein are systems and components for medical imaging and/ormedical treatment. In some embodiments, the medical system may includeone or more modalities including Digital Subtraction Angiography (DSA),Magnetic Resonance Imaging (MRI), Magnetic Resonance Angiography (MRA),Computed tomography (CT), Computed Tomography Angiography (CTA),Ultrasound Scanning (US), Positron Emission Tomography (PET),Single-Photon Emission Computerized Tomography (SPECT), CT-MR, CT-PET,CE-SPECT, DSA-MR, PET-MR, PET-US, SPECT-US, TMS (transcranial magneticstimulation)-MR, US-CT, US-MR, X-ray-CT, X-ray-MR, X-ray-portal,X-ray-US, Video-CT, Vide-US, or the like, or any combination thereof.

An aspect of the present disclosure relates to systems and methods forcontrolling a medical device. The medical device may include a medicalimaging device, e.g., an MRI device. In some embodiments, the system mayinclude one or more radars, and one or more cameras. The medical devicemay be controlled by fusing data acquired by the one or more radars andthe one or more cameras. For example, the system may determine firstdata regarding a first motion of a subject by processing a plurality ofimage frames acquired by the one or more cameras. The system maydetermine second data regarding second data regarding a second motion ofthe subject by processing radar echo data acquired by the one or moreradars. The radar echo data may be corrected based on the first data. Insome embodiments, the first motion may include a rigid motion of thesubject, and the second motion may include a physiological motion. Thesystem may extract physiological motion information based on the firstdata and the second data. For example, the physiological motioninformation may include cardiac motion data and/or respiratory motiondata. The system may control, based on the physiological motioninformation, the medical device in order to reduce or aovid the effectof motion artifacts in, e.g., imaging, delivery of a treatment dosage(e.g., a radiation beam toward a target region).

The following description is provided with reference to exemplaryembodiments that the medical device include an imaging device (e.g., ascanner) unless otherwise stated. However, it is understood that it isfor illustration purposes only and not intended to limit the scope ofthe present disclosure. The system and method disclosed herein may besuitable for other applications. Merely by way of example, the medicaldevice may include a radiotherapy device (an image-guided radiotherapy(IGRT) device); the system and method for identifying a physiologicalmotion may be used in controlling the delivery of a radiation beam inradiotherapy.

FIG. 1 is a schematic diagram illustrating an exemplary medical systemaccording to some embodiments of the present disclosure. As shown inFIG. 1 , medical system 100 may include a medical device 110, aprocessing device 120, a storage device 130, one or more terminals 140,and a network 150. The components in the medical system 100 may beconnected in one or more of various ways. Merely by way of example, asillustrated in FIG. 1 , the medical device 110 may be connected to theprocessing device 120 through the network 150. As another example, themedical device 110 may be connected to the processing device 120directly as indicated by the bi-directional arrow in dotted lineslinking the medical device 110 and the processing device 120. As afurther example, the storage device 130 may be connected to theprocessing device 120 directly or through the network 150. As still afurther example, one or more terminals 140 may be connected to theprocessing device 120 directly (as indicated by the bi-directional arrowin dotted lines linking the terminal 140 and the processing device 120)or through the network 150.

The medical device 110 may generate or provide image data by scanning asubject or at least a part of the subject. In some embodiments, themedical device 110 may be a medical imaging device, for example, apositron emission tomography (PET) device, a single photon emissioncomputed tomography (SPECT) device, a computed tomography CT device, amagnetic resonance imaging (MRI) device, a radiation therapy (RT)device, or the like, or any combination thereof. In some embodiments,the medical device 110 may include a single-modality scanner. Thesingle-modality scanner may include, for example, a magnetic resonanceimaging (MRI) scanner 110-1, a computed tomography (CT) scanner 110-2,and/ or a positron emission tomography (PET) scanner 110-3. In someembodiments, the medical device 110 may include both the CT scanner110-2 and the PET scanner 110-3. In some embodiments, image data ofdifferent modalities related to the subject, such as CT image data andPET image data, may be acquired using different scanners separately. Insome embodiments, the medical device 110 may include a multi-modalityscanner. The multi-modality scanner may include a positron emissiontomography-computed tomography (PET-CT) scanner, a positron emissiontomography-magnetic resonance imaging (PET-MRI) scanner, or the like, orany combination thereof. The multi-modality scanner may performmulti-modality imaging simultaneously. For example, the PET-CT scannermay generate structural X-ray CT image data and functional PET imagedata simultaneously in a single scan. The PET-MRI scanner may generateMRI data and PET data simultaneously in a single scan. In someembodiments, the medical device 110 may include an image-guidedradiotherapy (IGRT) device (not shown in FIG. 1 ). For example, the IGRTdevice may include a positron emission tomography-radiotherapy (PET-RT)device, or a magnetic resonance imaging-radiotherapy (MRI-RT) device,etc.

In some embodiments, the subject may include a body, a substance, or thelike, or any combination thereof. In some embodiments, the subject mayinclude a specific portion of a body, such as a head, a thorax, anabdomen, or the like, or any combination thereof. In some embodiments,the subject may include a specific organ, such as an esophagus, atrachea, a bronchus, a stomach, a gallbladder, a small intestine, acolon, a bladder, a ureter, a uterus, a fallopian tube, etc. In someembodiments, the subject may include a physical model (e.g., a waterphantom). In the present disclosure, “object” and “subject” are usedinterchangeably. In some embodiments, the medical device 110 may includea scanning table. The subject may be placed on the scanning table forimaging.

In some embodiments, the medical device 110 may transmit the image datavia the network 150 to the processing device 120, the storage device130, and/or the terminal(s) 140. For example, the image data may be sentto the processing device 120 for further processing, or may be stored inthe storage device 130. In some embodiments, the medical device 110 maybe configured to scan the subject or at least a part of the subject inresponse to a control signal generated by the processing device 120.

The processing device 120 may process data and/or information obtainedfrom the medical device 110, the storage device 130, and/or theterminal(s) 140. For example, the processing device 120 may obtain firstdata regarding a first motion of the subject through one or more camerasdisposed in the medical device 110. The processing device 120 may obtainsecond data regarding a second motion of the subject through one or moreradars disposed in the medical device 110. The processing device 120 maygenerate a control signal based on the first data and the second data.As another example, the processing device 120 may generate an image(e.g., an MR image) by reconstructing scan data acquired by the medicaldevice 110 (e.g., an MRI device).

In some embodiments, the processing device 120 may be a single server ora server group. The server group may be centralized or distributed. Insome embodiments, the processing device 120 may be local or remote. Forexample, the processing device 120 may access information and/or datafrom the medical device 110, the storage device 130, and/or theterminal(s) 140 via the network 150. As another example, the processingdevice 120 may be directly connected to the medical device 110, theterminal(s) 140, and/or the storage device 130 to access informationand/or data. In some embodiments, the processing device 120 may beimplemented on a cloud platform. For example, the cloud platform mayinclude a private cloud, a public cloud, a hybrid cloud, a communitycloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like,or a combination thereof.

The storage device 130 may store data, instructions, and/or any otherinformation. In some embodiments, the storage device 130 may store dataobtained from the medical device 110, the processing device 120, and/orthe terminal(s) 140. In some embodiments, the storage device 130 maystore data and/or instructions that the processing device 120 mayexecute or use to perform exemplary methods described in the presentdisclosure. In some embodiments, the storage device 130 may include amass storage device, a removable storage device, a volatileread-and-write memory, a read-only memory (ROM), or the like, or anycombination thereof. Exemplary mass storage may include a magnetic disk,an optical disk, a solid-state drive, etc. Exemplary removable storagemay include a flash drive, a floppy disk, an optical disk, a memorycard, a zip disk, a magnetic tape, etc. Exemplary volatileread-and-write memory may include a random access memory (RAM).Exemplary RAM may include a dynamic RAM (DRAM), a double date ratesynchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristorRAM (T-RAM), and a zero-capacitor RAM (Z-RAM), etc. Exemplary ROM mayinclude a mask ROM (MROM), a programmable ROM (PROM), an erasableprogrammable ROM (EPROM), an electrically erasable programmable ROM(EEPROM), a compact disk ROM (CD-ROM), and a digital versatile disk ROM,etc. In some embodiments, the storage device 130 may be implemented on acloud platform as described elsewhere in the disclosure. Merely by wayof example, the cloud platform may include a private cloud, a publiccloud, a hybrid cloud, a community cloud, a distributed cloud, aninter-cloud, a multi-cloud, or the like, or any combination thereof.

In some embodiments, the storage device 130 may be connected to thenetwork 150 to communicate with one or more other components in themedical system 100 (e.g., the processing device 120, the terminal(s)140, etc.). One or more components in the medical system 100 may accessthe data or instructions stored in the storage device 130 via thenetwork 150. In some embodiments, the storage device 130 may be part ofthe processing device 120.

The terminal(s) 140 may be connected to and/or communicate with themedical device 110, the processing device 120, and/or the storage device130. For example, the terminal(s) 140 may obtain a processed image fromthe processing device 120. As another example, the terminal(s) 140 mayobtain scan data acquired by the medical device 110 and transmit thescan data to the processing device 120 to be processed. In someembodiments, the terminal(s) 140 may include a mobile device 140-1, atablet computer 140-2, a laptop computer 140-3, or the like, or anycombination thereof. For example, the mobile device 140-1 may include amobile phone, a personal digital assistance (PDA), a gaming device, anavigation device, a point of sale (POS) device, a laptop, a tabletcomputer, a desktop, or the like, or any combination thereof. In someembodiments, the terminal(s) 140 may include an input device, an outputdevice, etc. The input device may include alphanumeric and other keysthat may be input via a keyboard, a touch screen (for example, withhaptics or tactile feedback), a speech input, an eye tracking input, abrain monitoring system, or any other comparable input mechanism. Theinput information received through the input device may be transmittedto the processing device 120 via, for example, a bus, for furtherprocessing. Other types of the input device may include a cursor controldevice, such as a mouse, a trackball, or cursor direction keys, etc. Theoutput device may include a display, a speaker, a printer, or the like,or a combination thereof. In some embodiments, the terminal(s) 140 maybe part of the processing device 120.

The network 150 may include any suitable network that can facilitateexchange of information and/or data for the medical system 100. In someembodiments, one or more components of the medical system 100 (e.g., themedical device 110, the processing device 120, the storage device 130,the terminal(s) 140, etc.) may communicate information and/or data withone or more other components of the medical system 100 via the network150. For example, the processing device 120 may obtain image data fromthe medical device 110 via the network 150. As another example, theprocessing device 120 may obtain user instruction(s) from theterminal(s) 140 via the network 150. The network 150 may be and/orinclude a public network (e.g., the Internet), a private network (e.g.,a local area network (LAN), a wide area network (WAN)), etc.), a wirednetwork (e.g., an Ethernet network), a wireless network (e.g., an 802.11network, a Wi-Fi network, etc.), a cellular network (e.g., a Long TermEvolution (LTE) network), a frame relay network, a virtual privatenetwork (VPN), a satellite network, a telephone network, routers, hubs,witches, server computers, and/or any combination thereof. For example,the network 150 may include a cable network, a wireline network, afiber-optic network, a telecommunications network, an intranet, awireless local area network (WLAN), a metropolitan area network (MAN), apublic telephone switched network (PSTN), a Bluetooth™ network, aZigBee™ network, a near field communication (NFC) network, or the like,or any combination thereof. In some embodiments, the network 150 mayinclude one or more network access points. For example, the network 150may include wired and/or wireless network access points such as basestations and/or internet exchange points through which one or morecomponents of the medical system 100 may be connected to the network 150to exchange data and/or information.

This description is intended to be illustrative, and not to limit thescope of the present disclosure. Many alternatives, modifications, andvariations will be apparent to those skilled in the art. The features,structures, methods, and other characteristics of the exemplaryembodiments described herein may be combined in various ways to obtainadditional and/or alternative exemplary embodiments. For example, thestorage device 130 may be a data storage including cloud computingplatforms, such as, a public cloud, a private cloud, a community cloud,and a hybrid cloud, etc. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 2 is a schematic diagram illustrating an exemplary medical deviceaccording to some embodiments of the present disclosure. As shown inFIG. 2 , medical device 220 may include a scanner 210, one or moreradars 220, one or more cameras 230, and a processing device 240. Thescanner 210 may be configured to scan a subject or at least a part ofthe subject, and acquire corresponding scan data. The one or more radars220 may be configured to acquire radar echo data from the subject. Insome embodiments, the radar echo data may include data related to aphysiological motion of the subject (hereinafter physiological motionrelated data). In some embodiments, the radar echo data may include thephysiological motion related data and data related to a rigid motion ofthe subject (hereinafter rigid motion related data). The one or morecameras 230 may be configured to acquire a plurality of image frames ofthe subject. In some embodiments, the rigid motion may be identifiedbased on at least a part of the plurality of image frames. Theprocessing device 240 may be configured to process data/signals acquiredby the one or more cameras 230 and the one or more radars 220 (e.g.,image data and radar echo data), and generate a control signal forcontrolling the scanner 210 to scan the subject. In some embodiments,the processing device 240 may be configured to reconstruct an imagebased on the scan data.

In some embodiments, the scanner 210 may include a CT device, an MRIdevice, a PET device, an ultrasonic device, an X-ray imaging device, orthe like. In some embodiments, the medical device 220 may include atreatment device, e.g., a radioation treatment device, instead of thescanner 210. For example, the imageing device 200 may be the IGRTdevice. The following description is provided with reference toexemplary embodiments that the medical device include a scanner 210 forillustration purposes and not intended to be limiting.

The scanner 210 may include various suitable medical imaging devices fordiagnosing and/or treating a disease, and not intended to be limiting.Taking the MRI device as an example, a magnetic resonance unit of theMRI device may include a magnet assembly, a gradient coil assembly, anda radiofrequency (RF) coil assembly. For example, the magnet assemblymay generate a main magnetic field for polarizing the subject to bescanned. The gradient coil assembly may generate a gradient magneticfield. The RF coil assembly may include a plurality of RF coils fortransmitting and/or receiving RF signals. In some embodiments, themagnetic resonance unit may form a cavity providing an examinationspace. The scanning table may move along the cavity. The subject may beplaced on the scanning table for MR imaging.

In some embodiments, the radar of the one or more radars 220 may atleast include an antenna and a processing component. In someembodiments, the antenna and the processing component may be integratedinto a single chip. In some embodiments, the antenna and the processingcomponent may be disposed separately. In some embodiments, the antennamay transmit radar signals to the subject within a coverage zone in aradar field. The antenna may receive radar echo signals reflected fromthe subject within the coverage zone. In some embodiments, a radar mayinclude multiple antennas. The detection angle of the antenna may beadjusted according to the position of the subject or at a part of thesubject. For example, a detectable region of the multiple antennas maybe designed to cover the subject at suitable detection angles (e.g., 60degrees, 70 degrees, 130 degrees, or 180 degrees) in order to acquirelarge-scale radar echo data. As another example, a detection region ofat a part of the multiple antennas may be designed to cover a region ofinterest (ROI) of the subject in order to acquire radar echo dataregarding the ROI (e.g., a thoracic and abdominal region). In someembodiments, the detection angle of the antenna may be a fixed angle(e.g., 60 degrees). In some embodiments, the radar may be a phased arrayradar having an antenna array forming by a plurality of antenna units.Each antenna unit may be controlled by a single phase shift switch. Thephase beams may be synthesized by controlling the phase beam emitted byeach antenna unit.

In some embodiments, the one or more radars 220 may be used to provide anon-invasive remote monitoring for the physiological motion. The one ormore radars 220 may be disposed on various suitable positions formonitoring the physiological motion. For example, the one or more radars220 may be disposed on a component of the scanner 210, such as, on an RFreceiving coil, in a cavity around the examination space, or on ascanning table. As another example, the one or more radars 220 may beattached to the subject's clothes (e.g., the position close to thethoracic and abdominal region). In some embodiments, the one or moreradars 220 may be disposed on a suitable position outside the medicaldevice, such as, on a ceiling of a treatment room, on the floor of thetreatment room, or a holder outside the medical device, etc.

In some embodiments, a distance between the radar and the subject may be0-25 meters (e.g., less than 5 meters). Alternatively, the distance maybe 1 millimeter to 3 meters, such as, 1 meter, or 2 meters.Alternatively, the distance may be 10 millimeters to 3000 millimeters,such as 100 millimeters to 2000 millimeters. The radar may emit radarbeams (e.g., electromagnetic waves) to irradiate the subject, andreceive radar echo signals reflected by the subject. In someembodiments, an emission frequency of the radar may be set as 1 GHz to100 GHz. For example, a low frequency range (e.g., 1 GHz to 50 GHz) maybe used to detect an interior movement inside the subject (e.g., acardiac movement, a diaphragm movement). A high frequency range of theradar (e.g., 50 GHz to 100 GHz) may be used to detect a body surfacemovement (e.g., a skin movement). In some embodiments, the emissionfrequency of the radar may be set as different frequency ranges so as toidentify various movements regarding the subject.

In some embodiments, the one or more radars 220 may include asingle-mode radar and/or a multi-mode radar. For example, thesingle-mode radar may include a continuous wave (CW) radar, anon-continuous wave radar (e.g., a ultra wideband (UWB) radar, or afrequency modulated continuous wave (FMCW) radar), a LIDAR, and so on.The multi-mode radar may include a CW-UWB radar, a CW-FMCW radar, or aUWB-FMCW radar, and so on. The types of the radar may be adjustedaccording to different scenarios. For example, the CW radar may beactivated to monitor the cardiac motion. As another example, the UWBradar may be activated to monitor the abdominal movement. As a furtherexample, a combined use of the CW radar and the UWB radar may be used todetect the radiation in various wavebands (e.g., in the millimeterwavelength range) that is emitted or reflected by the subject.

In some embodiments, the one or more radars 220 may be configured todetect radar echo signals from the subject. The radar echo signals mayinclude motion information regarding the subject (e.g., rigid motioninformation and/or physiological motion information). For example, therigid motion may include a translational and/or rotational motion of thesubject. Exemplary rigid motion may include a pose motion of thesubject, such as the rotating or nodding of the head of the subject,legs motion, hands motion, and so on. As another example, thephysiological motion may include respiratory motion (or breathingmotion), heart motion (or cardiac motion), and so on. In someembodiments, the radar echo signals may be image data or point clouddata. For example, the radar echo signals may be a three-dimensionalimage data regarding the head of the subject. As another example, theradar echo signals may be point cloud data including locationinformation of one or more characteristic points (e.g., the highestpoint coordinates and the lowest point coordinates of the abdominal). Insome embodiments, the radar echo signals may be desired to determinephysiological motion of the subject. One or more parameters (e.g.,cardiac motion data or respiratory motion data) of the physiologicalmotion may be used to control the scan of the medical device, which mayreduce or avoid motion artifacts (e.g., motion artifacts caused by thecardiac motion or the breathing motion) in a reconstructed image.However, the radar echo signals may include disturbed signals caused bythe rigid motion of the subject. The disturbed signals may be filteredin a subsequent processing operation. The use of the one or more radars220 may be an effective physiological motion detection means instead ofconventional means. For example, the conventional means may require oneor more electrodes and/or respiratory zones attached to the body of thesubject in order to detect the physiological motion of the subject,which may cause more or less discomfortable feeling for some subjects.By contrast, the use of the radar may reduce the discomfortable feeling,and ignore an installing time of the electrodes and/or respiratoryzones, which may reduce the scan time of the medical device.

In some embodiment, the design of the one or more cameras 230 may aim atobtaining rigid motion information. The camera of the one or morecameras 230 may include a three-dimensional (3D) camera, such as a timeof flight (TOF) camera, a structural light camera, a binocular camera, aLIDAR camera, or the like, or any combination thereof. The 3D camera maybe configured to capture position and/or depth information of an object.The 3D image or model may be reconstructed based on the capturedposition and/or depth information. It should be noted that light signalscaptured by the camera do not interfere with the radar echo signalscaptured by the radar. In some embodiments, the one or more cameras 230may include various commercially available image capture devices forimaging. For example, the one or more cameras 230 may be configured togenerate video images of the subject. The video images may include asequence of image frames of the subject. The rigid motion may beidentified by analyzing the sequence of image frames. In someembodiments, motion parameters regarding the rigid motion may be used tocorrect the radar echo data captured by the one or more radars 220. Thecorrected radar echo data may be used to generate accurate physiologicalinformation.

In some embodiments, the one or more cameras 230 may be disposed onvarious suitable positions for monitoring the rigid motion of thesubject. For example, the one or more cameras 230 may be disposed on acomponent of the scanner 210, such as, on an RF receiving coil, in acavity around the examination space, or on a scanning table. In someembodiments, the one or more cameras 230 and the one or more radars 220may be disposed at the same position in the examination space of thescanner 210. In some embodiments, the one or more cameras 230 and theone or more radars 220 may be disposed at different positions,respectively. For example, the one or more radars 220 may be disposed inthe cavity, and the one or more cameras 230 may be disposed on the RFreceiving coil. In some embodiments, positions of the one or morecameras 230 and the one or more radars 220 may be adjusted according tothe position of the subject, in order to detect corresponding signalsfrom the subject within their coverage zone. The use of one or morecameras 230 is also a non-contactless detection for the subject, whichmay reduce the discomfortable feeling of the subject by contract withthe contactless detection. In some embodiments, the one or more cameras230 may be aligned at a certain angle towards the subject or at least apart of the subject, in order to obtain a larger detection angle and alarge-scale detection data.

In some embodiments, the radar and the camera may be integrated into aradar-camera sensor module (not shown in FIG. 2 ). The integratedradar-camera sensor module includes a radar component for transmittingradar signals and receiving reflected radar signals (i.e., radar echosignals) that are reflected from one or more objects within a coveragezone in a radar field. The integrated radar-camera sensor module furtherincludes a camera component for capturing images based on light wavesthat are seen and captured within a coverage zone in a camera field. Insome embodiments, the radar component and the camera component may behoused in a common housing. The common housing may be made of variousmaterials, such as rigid materials, or non-rigid materials. In someembodiments, the radar component and the camera component may be coupledto processing circuits for processing the captured images and thereceived reflected radar signals, such as, fusing the captured imagesand the reflected radar signals. The fused data may be used to indicatevital signs of the subject, such as respiratory motion, heart motion.

In some embodiments, the camera component may include a plurality ofoptical elements and an imager. The camera component may include acommercially available image capture device for imaging. For example,the camera component may be configured to generate video images of thesubject. The video images may include a plurality of image frames. Insome embodiments, the radar component may include a radar transceivercoupled to an antenna. The transceiver and antenna operate to transmitradar signals within the desired coverage zone, and to receive radarecho signals reflected from the subject within the coverage zone. Insome embodiments, the radar component may transmit a single fan-shapedradar beam and form multiple beams by receiving digital beamforming. Insome embodiments, the antenna may include a vertical polarizationantenna and/or a horizontal polarization antenna. The verticalpolarization antenna may provide vertical polarization of the radarsignals. The horizontal polarization antenna may provide horizontalpolarization of the radar signals.

FIG. 3 is a schematic diagram illustrating an exemplary work schemeaccording to some embodiments of the present disclosure. As shown inFIG. 3 , a radar 220 and two cameras 230 may be arranged in theexamination space of the medical device. The radar 220 may be configuredto acquire radar echo signals from the subject. The radar echo signalsmay provide information related to physiological motion of the subject(e.g., respiratory motion, or heart motion). In some cases, the radarecho signals may include disturbed signals caused by rigid motion of thesubject (e.g., a head movement, leg movement, hand movement, etc). Thetwo cameras 230 may be configured to capture a plurality of image framesincluded the subject. The plurality of image frames may provideinformation related to rigid motion of the subject. In some embodiments,the processing device 240 may perform one or more fusion operations forthe plurality of image frames and the radar echo signals. For example,the one or more fusion operations may include image frames analysis andradar echo signals analysis. In some embodiments, the processing device240 may perform the image frames analysis to determine one or moremotion parameters regarding the rigid motion. The determined motionparameters may be transformed into a coordinate system corresponding tothe radar 220. In some embodiments, the processing device 240 mayperform the radar echo signals analysis to determine data related to thephysiological motion, such as heart beat signal and/or respiratorysignal as shown in FIG. 3 . In some embodiments, the heart beat signalmay be an electrocardiogram (ECG) signal. In some embodiments, the radarecho signal analysis may include one or more operations for correctingthe radar echo signals based on the motion parameters regarding therigid motion. For example, the processing device 240 may correct theradar echo signals by filtering out the disturbed signals caused by therigid motion, and extract the heart beat signals (e.g., ECG signals) andthe respiratory signals. In some embodiments, the extracted heat beatsignals and/or respiratory signals may be used to control one or morescan operations of the medical device (e.g., the MRI device). In someembodiments, the processing device 240 may reconstruct a medical image(e.g., an MR image) based on the scan data acquired by the medicaldevice (e.g., the MRI device). More descriptions about the image framesanalysis and the radar echo signal analysis may be found elsewhere inthe present disclosure (e.g., FIG. 7A and FIG. 8 , and the descriptionsthereof).

FIG. 4 is a schematic diagram illustrating an exemplary data acquisitionaccording to some embodiments of the present disclosure. In someembodiments, the one or more radars 220 and the one or more cameras 230may acquire corresponding data simultaneously in response to a clocksignal from a system clock of the medical device. In some embodiments,as illustrated in FIG. 4 , the one or more radars 220 and the one ormore cameras 230 may alternately capture corresponding data regardingvarious parts of the subject at different time points. In someembodiments, the detection angles of the one or more cameras 230 and theone or more radars 220 may be set according to a region of interest(ROI) of the subject. The ROI of the subject may be any part of thesubject, such as, the head, the chest, a leg, and so on. For example,when the ROI is the chest region, the detection angle of the camera maybe set as 60 degrees, and the detection angle of the radar may be set as90 degrees. The one or more cameras 230 and the one or more radars 220may acquire data within their own coverage zone. The acquired data maybe used to characterize the motion of the subject (e.g., thephysiological motion, or the rigid motion).

FIG. 5 is a block diagram illustrating an exemplary medical imagingsystem according to some embodiments of the present disclosure. Asillustrated in FIG. 5 , the medical imaging system 500 may include amedical device 510, a radar 520, a camera 530, a processing device 540,a storage device 550 and a terminal device 560. In some embodiments, themedical device 510 may scan a subject or at a part of the subject (e.g.,an ROI of the subject). The radar 520 may acquire radar echo signalsfrom the subject. The camera 530 may acquire a plurality of image framesincluding the subject. The processing device 540 may process the radarecho signals and the plurality of image frames to generate a controlsignal for controlling the medical device. In response to the controlsignal, the medical device 510 may obtain accurate scan data. Theprocessing device 540 may reconstruct a medical image based on the scandata. In some embodiments, one or more components of the medical imagingsystem 500 (e.g., the camera 530, the radar 520 or the medical device510) may be connected by various means. For example, the medical device510, the radar 520, the camera 530, the terminal device 560 and/or thestorage device 550 may be connected to the processing device 540 via anetwork (e.g., the network 150), or be connected to the processingdevice 540 directly.

In some embodiments, the medical device 510 may be used in medicaltreatments and/or diagnosis. The medical device 510 may be the same asor similar to the medical device 110 as illustrated in FIG. 1 . Takingthe IGRT device as an example, the IGRT device may irradiate a target(e.g., a lesion (or a tumor)) using various radioactive rays, such as,X-rays, y-rays, electron lines, proton beams, and so on. The IGRT devicemay include an accelerator (e.g., a linear accelerator or a cyclotron).The linear accelerator may generate and emit the radioactive rays (e.g.,X-rays) to the target for killing cancer cells. A therapeutic effect onthe tumor may be achieved. The accelerator may rotate with a gantry ofthe IGRT device in the clockwise or counterclockwise direction around anaxis of the rack. The IGRT device may include a treatment table forsupporting the subject. In some embodiments, the treatment table may bea six-dimensional platform capable of performing a linear motion inthree directions of x, y, and z, and a rotational motion in threedirections of x, y, and z. The treatment table may move the subject to acorresponding position (e.g., a target zone) accurately and/or quickly.

In some embodiments, the radar 520 may be the same as or similar to theradar 220. For example, the radar 520 may include a single-mode radarand/or a multi-mode radar. For example, the single-mode radar mayinclude a continuous wave (CW) radar, a non-continuous wave radar (e.g.,an ultra wideband (UWB) radar, or a frequency modulated continuous wave(FMCW) radar), a light detection and ranging (LIDAR) device, and so on.The multi-mode radar may include a CW-UWB radar, a CW-FMCW radar, or anUWB-FMCW radar, and so on. In some embodiments, the camera 530 may bethe same as or similar to the camera 230. For example, the camera mayinclude a three-dimensional (3D) camera, such as a time of flight (TOF)camera, a structured light camera, a binocular camera, a LIDAR camera,or the like, or any combination thereof. More descriptions of the radarand the camera may be found elsewhere in the present disclosure. See,e.g., FIG. 2 , and the descriptions thereof.

In some embodiments, the processing device 540 may process data and/orinformation obtained from the medical device 510, the terminal device560, the storage device 550, the camera 530, and/or the radar 520. Forexample, the processing device 540 may determine first data regarding afirst motion of the subject. The first motion may include a rigid motionof the subject. The first data may be rigid motion related data, suchas, motion parameters. As another example, the processing device 540 maydetermine second data regarding a second motion of the subject. Thesecond motion may include a physiological motion of the subject. Thesecond data may be physiological motion related data, such as cardiacmotion data or respiratory motion data. As a further example, theprocessing device 540 may generate a control signal for controlling thedevice based on the first data and the second data. In some embodiments,the processing device 540 may be the same as or similar to theprocessing device 120 illustrated in FIG. 1 . For example, theprocessing device 540 may be a single server or a server group. Asanother example, the processing device 540 may include a centralprocessing unit (CPU), an application-specific integrated circuit(ASIC), an application-specific instruction-set processor (ASIP), agraphics processing unit (GPU), a physics processing unit (PPU), adigital signal processor (DSP), a field-programmable gate array (FPGA),a programmable logic device (PLD), a controller, a microcontroller unit,a reduced instruction-set computer (RISC), a microprocessor, or thelike, or any combination thereof.

In some embodiments, the storage device 550 may store data and/orinstructions. In some embodiments, the storage device 550 may store dataobtained from medical device 510, the radar 520, the camera 530, theprocessing device 540, and the terminal device 560. In some embodiments,the storage device 550 may store data and/or instructions that theprocessing device 540 may execute or use to perform exemplary methodsdescribed in the present disclosure. The storage device 550 may be thesame as or similar to the storage device 130 illustrated in FIG. 1 . Forexample, the storage device 550 may include a mass storage device, aremovable storage device, a volatile read-and-write memory, a read-onlymemory (ROM), or the like, or any combination thereof.

In some embodiments, the terminal device 560 may be connected to and/orcommunicate with the medical device 510, the radar 520, the camera 530,the processing device 540 and/or the storage device 550. For example,the terminal device 560 may obtain a processed image from the processingdevice 540. As another example, the terminal device 560 may obtain scandata acquired by the medical device 510 and transmit the scan data tothe processing device 540 to be processed. In some embodiments, theterminal device 560 may be the same as or similar to the terminal(s) 140illustrated in FIG. 1 . For example, the terminal device 560 may includea mobile device, a tablet computer, a laptop computer, or the like, orany combination thereof.

This description is intended to be illustrative, and not to limit thescope of the present disclosure. Many alternatives, modifications, andvariations will be apparent to those skilled in the art. The features,structures, methods, and other characteristics of the exemplaryembodiments described herein may be combined in various ways to obtainadditional and/or alternative exemplary embodiments. For example, thestorage device 550 may be a data storage including cloud computingplatforms, such as, a public cloud, a private cloud, a community cloud,and a hybrid cloud, etc. However, those variations and modifications donot depart from the scope of the present disclosure.

FIG. 6 is a block diagram illustrating an exemplary processing deviceaccording to some embodiments of the present disclosure. In someembodiments, the processing device 540 may be in communication with acomputer-readable storage medium (e.g., the storage device 550illustrated in FIG. 5 , the storage device 130 illustrated in FIG. 1 .)and may execute instructions stored in the computer-readable storagemedium. The processing device 540 may include an acquisition module 602,a first data determination module 604, a second data determinationmodule 606, a control module 608, and a reconstruction module 610.

The acquisition module 602 may be configured to acquire data from one ormore modules of the processing device 540. In some embodiments, theacquisition module 602 may obtain first data regarding a first motion ofa subject in an examination space of a medical device. In someembodiments, the first data determination module 604 may determine thefirst data regarding the first motion. The acquisition module 602 mayobtain the first data from the first data determination module 604. Insome embodiments, the acquisition module 602 may acquire a plurality ofimage frames of the subject through one or more cameras. The one or morecameras may be installed on the medical device. The plurality of imageframes may be used to determine the first data. In some embodiments, theacquisition module 602 may obtain second data regarding a second motionof the subject. In some embodiments, the second data determinationmodule 606 may determine the second data regarding the second motion ofthe subject. The acquisition module 602 may obtain the second data fromthe second data determination module 606. In some embodiments, theacquisition module 602 may acquire radar echo data through one or moreradars. The one or more radars may be installed on the medical device.The radar echo data may be used to determine the second data. In someembodiments, the first motion may include a rigid motion, and the secondmotion may include a physiological motion.

The first data determination module 604 may determine, based on at leasta part of the plurality of image frames, first data including one ormore motion parameters. For example, the first data determination module604 may process the plurality of image frames to identify the rigidmotion of the subject. For example, the first data determination module604 may determine one or more motion parameters of the first motionbased on at least a part of the plurality of image frames. In someembodiments, the one or more motion parameters may include athree-dimensional translation matrix and/or a three dimensional rotationmatrix. In some embodiments, the first data determination module 604 maydetermine the one or more motion parameters using an image registrationtechnique. Exemplary image registration technique may include but notlimited to a pixel-based registration algorithm, a feature-basedregistration algorithm, a contour-based registration algorithm, a mutualinformation-based registration algorithm, and so on. More descriptionsof the determination of the first data may be found elsewhere in thepresent disclosure (e.g., FIG. 8 and the description thereof).

The second data determination module 606 may determine the second dataregarding the second motion of the subject. In some embodiments, thesecond motion may include a physiological motion of the subject. Thephysiological motion may include a heart motion and/or respiratorymotion of the subject. In some embodiments, the second datadetermination module 606 may process the radar echo data to identify thephysiological motion of the subject. For example, the second datadetermination module 606 may correct the acquired radar echo data byfiltering out disturbed information caused by the rigid motion. Thesecond data determination module 606 may extract the second data fromthe corrected radar echo data. The second data may include cardiacmotion data or respiratory motion data. More descriptions of thedetermination of the second data may be found elsewhere in the presentdisclosure (e.g., FIG. 8 and the description thereof).

The control module 608 may generate, based on the first data and thesecond data, a control signal for controlling the medical device to scanat least a part of the subject. More specifically, the control module608 may generate the control signal based on the cardiac motion dataand/or the respiratory motion data. The cardiac motion data and/or therespiratory motion data may be determined based on the first data andthe second data. In some embodiments, the control module 608 maygenerate the control signal using a gating technique. The gatingtechnique may include a cardiac gating and a respiratory gating. Inresponse to the control signal, the medical device may be directed toscan the subject or at least a part of the subject.

The reconstruction module 610 may reconstruct a medical image based onthe scan data acquired by the medical device. For example, thereconstruction module 610 may reconstruct the image using one or morereconstruction algorithms. The one or more reconstruction algorithms mayinclude but not limited to a 2-dimensional Fourier transform technique,a back projection technique (e.g., a convolution back projectiontechnique, a filtered back projection technique), an iterationreconstruction technique, etc. Examples of iterative reconstructiontechniques may include a simultaneous algebraic reconstruction technique(SART), a simultaneous iterative reconstruction technique (SIRT), anordered subset convex technique (OSC), ordered subset maximum likelihoodmethodologies, an ordered subset expectation maximization (OSEM)methodology, an adaptive statistical iterative reconstruction technique(ASIR) methodology, a least squares QR methodology, an expectationmaximization (EM) methodology, an OS-separable paraboloidal surrogatestechnique (OS-SPS), an algebraic reconstruction technique (ART), aKacsmarz reconstruction technique, or any other iterative reconstructiontechnique or methodology that meets application-specific requirements.

It should be noted that the descriptions above in relation to processingdevice 540 are provided for the purposes of illustration, and notintended to limit the scope of the present disclosure. For personshaving ordinary skills in the art, various variations and modificationsmay be conducted under the guidance of the present disclosure. However,those variations and modifications do not depart the scope of thepresent disclosure. In some embodiments, the processing device 540 mayinclude one or more other modules. For example, the processing device540 may include a storage module to store data generated by the modulesin the processing device 540. In some embodiments, any two of themodules may be combined as a single module, and any one of the modulesmay be divided into two or more units.

FIG. 7A is a flowchart illustrating an exemplary process for controllinga medical device according to some embodiments of the presentdisclosure. Process 700 may be implemented in the medical system 100illustrated in FIG. 1 or the medical imaging system 500 illustrated inFIG. 5 . For example, the process 700 may be stored in the storagedevice 130 and/or the storage device 550 in the form of instructions(e.g., an application), and invoked and/or executed by the processingdevice 120 (e.g., the processing device 540 illustrated in FIG. 5 , orone or more modules in the processing device 540 illustrated in FIG. 6). The operations of the illustrated process presented below areintended to be illustrative. In some embodiments, the process 700 may beaccomplished with one or more additional operations not described,and/or without one or more of the operations discussed. Additionally,the order in which the operations of the process 700 as illustrated inFIG. 7 and described below is not intended to be limiting.

In 702, the processing device (e.g., the acquisition module 602 of theprocessing device 540) may obtain first data regarding a first motion ofa subject in an examination space of a medical device. In someembodiments, the first data determination module 604 of the processingdevice 540 may determine the first data regarding the first motion ofthe subject in the examination space of the medical device. Theacquisition module 602 may obtain the first data from the first datadetermination module 604. In some embodiments, the first motion mayrefer to a rigid motion. The rigid motion may include a translationaland/or rotational motion of the subject. Exemplary rigid motion mayinclude a pose motion of the subject, such as the rotating or nodding ofthe head of the subject, a motion of a leg, a motion of a hand, and soon. The first data may refer to data related to the first motion (e.g.,the rigid motion). Hereinafter the first data may be referred to asfirst motion related data, rigid motion related data, or pose motionrelated data.

In some embodiments, the acquisition module 602 may acquire, via one ormore cameras (e.g., the one or more cameras 230, or the camera 530), aplurality of image frames regarding the first motion of the subject inthe examination space of the medical device. The one or more cameras maycapture the plurality of image frames including the subject. Theplurality of image frames may be sent to the acquisition module 602. Thefirst data determination module 604 may process the plurality of imageframes to identify the rigid motion of the subject. For example, thefirst data determination module 604 may determine one or more motionparameters of the first motion based on at least a part of the pluralityof image frames. In some embodiments, the one or more motion parametersmay include a three-dimensional translation matrix and/or a threedimensional rotation matrix. In some embodiments, the first datadetermination module 604 may determine the one or more motion parametersusing an image registration technique. Exemplary image registrationtechniques may include a pixel-based registration algorithm, afeature-based registration algorithm, a contour-based registrationalgorithm, a mutual information-based registration algorithm, and so on.More descriptions of the determination of the first data may be foundelsewhere in the present disclosure (e.g., FIG. 8 and the descriptionthereof).

In 704, the processing device (e.g., the acquisition module 602 of theprocessing device 540) may obtain second data regarding a second motionof the subject. In some embodiments, the second data determinationmodule 606 of the processing device 540 may determine the second dataregarding the second motion of the subject. The acquisition module 602may obtain the second data from the second data determination module606. In some embodiments, the second motion may include a physiologicalmotion of the subject. The physiological motion may include a cardiacmotion, a respiratory motion, or the like, of the subject. The seconddata may refer to data related to the second motion (e.g., thephysiological motion). Hereinafter the second data may be referred to assecond motion related data, or physiological motion related data.

In some embodiments, the acquisition module 602 may acquire, via one ormore radars (e.g., the one or more radars 220, or the radar 520), radarecho data from the subject. For example, the one or more radars may emitradar signals to the subject or at least a part of the subject, andreceive the radar echo signals reflected from the subject. The radarecho signals may include motion information of the subject. The motioninformation may include not only the physiological motion information,but also the rigid motion information. In this case, the radar echosignals caused by the rigid motion may be designated as disturbedsignals. The acquired radar echo data may be sent to the acquisitionmodule 602. The second data determination module 606 may process theradar echo data to identify the physiological motion of the subject. Forexample, the second data determination module 606 may correct theacquired radar echo data by filtering out the disturbed informationcaused by the rigid motion. The second data determination module 606 mayextract the second data from the corrected radar echo data. The seconddata may include cardiac motion data or respiratory motion data. Moredescriptions of the determination of the second data may be foundelsewhere in the present disclosure (e.g., FIG. 8 and the descriptionthereof).

In 706, the processing device (e.g., a control module 608 of theprocessing device 540) may generate, based on the first data and thesecond data, a control signal for controlling the medical device to scanat least a part of the subject. In some embodiments, the processingdevice 540 may generate accurate cardiac motion data and/or respiratorymotion data based on the first data and the second data. The accuratecardiac motion data and respiratory motion data may facilitate to reduceor avoid motion artifacts (e.g., cardiac motion artifacts or respiratorymotion artifacts) in a reconstructed image. For example, the second datadetermination module 606 may correct the radar echo data according tothe one or more motion parameters of the first motion. The disturbedcomponent of the radar echo data may be removed by the correction. Thecardiac motion data and/or the respiratory motion data extracted fromthe corrected radar echo data may be more accurate than the uncorrectedradar echo data. In some embodiments, the control module 608 maygenerate the control signal using a gating technique. The gatingtechnique may be used for synchronization of signal (e.g., an MR signal)acquisition to the cardiac and/or respiratory cycle.

In some embodiments, the gating technique may include a cardiac gatingand/or a respiratory gating. For example, the cardiac gating may bebased on cardiac motion data (e.g., an ECG signal). The ECG signal mayshow a plurality of cardiac cycles. Each cardiac cycle may correspond toa heartbeat. In some embodiments, one cardiac cycle may be a timeinterval between two R-waves of the ECG signal. Merely by way ofexample, FIG. 7B illustrates an exemplary cardiac gating according tosome embodiments of the present disclosure. As illustrated in FIG. 7B,in a specific time point between two R-waves (e.g., an end of a triggerdelay, or a beginning of an acquisition window), the control module 608may generate a control signal (e.g., a gating signal) for triggering themedical device (e.g., the MRI device) to scan in order to acquire scandata. The trigger delay may be defined as the time interval between thefirst R-wave and the beginning of data acquisition. The scan data may beacquired during the acquisition window. The control module 608 maygenerate the control signal for each scan based on the ECG signal. Theuse of the cardiac gating technique may facilitate to reduce or avoidthe cardiac motion artifacts.

As another example, FIG. 7C illustrates an exemplary respiratory gatingaccording to some embodiments of the present disclosure. The respiratorygating may be based on respiratory data. The respiratory data may show aplurality of respiratory cycles as shown in FIG. 7C. The respiratorycycle may be a cycle of inspiration and expiration. The acquisitionwindow may be defined as a time interval when an amplitude of therespiratory signal is within the gating width. The scan data may beacquired during the acquisition window. In some embodiments, when theamplitude of the respiratory signal is within the gating width, thecontrol module 608 may generate a control signal (e.g., a gating signal)for triggering the medical device (e.g., the MRI device) to scan andacquiring scan data during expiration (when least diaphragmatic movementoccurs).

In some embodiments, the gating technique may be used to control variousmedical devices for reducing motion artifacts. For example, an ECG-gatedtechnique may be used to perform a CT scan (e.g., for cardiac imaging).As another example, the respiratory and cardiac gating technique may beused to perform a PET scan (e.g., for cardiac PET imaging). As a furtherexample, the respiratory gating may be used to monitor the movement of atumor during normal breathing of a subject in a radiotherapy session.When the tumor moves outside a target field, a gating signal for turningoff the treatment beam may be generated according to the respiratorygating.

In 708, the processing device (e.g., the acquisition module 602 of theprocessing device 540) may obtain scan data acquired by the medicaldevice. For example, in response to the control signal, the medicaldevice may be directed to scan the subject or at least part of thesubject. In some embodiments, the scan data may be stored in the storagedevice 130. The acquisition module 602 may send the scan data to thereconstruction module 610 for further processing.

In 710, the processing device (e.g., the reconstruction module 610 ofthe processing device 540) may reconstruct a medical image based on thescan data. In some embodiments, the reconstruction module 610 mayreconstruct the image using one or more reconstruction algorithms. Forexample, the one or more reconstruction algorithms may include a2-dimensional Fourier transform technique, a back projection technique(e.g., a convolution back projection technique, a filtered backprojection technique), an iteration reconstruction technique, etc.Examples of iterative reconstruction techniques may include asimultaneous algebraic reconstruction technique (SART), a simultaneousiterative reconstruction technique (SIRT), an ordered subset convextechnique (OSC), ordered subset maximum likelihood methodologies, anordered subset expectation maximization (OSEM) methodology, an adaptivestatistical iterative reconstruction technique (ASIR) methodology, aleast squares QR methodology, an expectation maximization (EM)methodology, an OS-separable paraboloidal surrogates technique (OS-SPS),an algebraic reconstruction technique (ART), a Kacsmarz reconstructiontechnique, or any other iterative reconstruction technique ormethodology that meets application-specific requirements.

It should be noted that the description of the process 700 is providedfor the purposes of illustration, and not intended to limit the scope ofthe present disclosure. For persons having ordinary skills in the art,various variations and modifications may be conducted under the teachingof the present disclosure. For example, operations 702 and 704 may beintegrated into a single operation. As another example, operations 704and 706 may be integrated into a single operation. However, thosevariations and modifications may not depart from the protecting of thepresent disclosure.

FIG. 8 is a flowchart illustrating an exemplary process for extractingphysiological motion related data according to some embodiments of thepresent disclosure. Process 800 may be implemented in the medical system100 illustrated in FIG. 1 or the medical imaging system 500 illustratedin FIG. 5 . For example, the process 800 may be stored in the storagedevice 130 and/or the storage device 550 in the form of instructions(e.g., an application), and invoked and/or executed by the processingdevice 120 (e.g., the processing device 540 illustrated in FIG. 5 , orone or more modules in the processing device 540 illustrated in FIG. 6). The operations of the illustrated process presented below areintended to be illustrative. In some embodiments, the process 800 may beaccomplished with one or more additional operations not described,and/or without one or more of the operations discussed. Additionally,the order in which the operations of the process 800 as illustrated inFIG. 8 and described below is not intended to be limiting.

In 802, the processing device (e.g., the acquisition module 602 of theprocessing device 540) may acquire a plurality of image frames regardinga first motion of a subject.

In some embodiments, the first motion may refer to a rigid motion. Therigid motion may include a translational and/or rotational motion of thesubject. Exemplary rigid motion may include a pose motion of thesubject, such as the rotating or nodding of the head of the subject, legmotion, hand motion, and so on. The rigid motion may be identified by asequence of image frames. In some embodiments, one or more cameras (orother image capture devices) installed on the medical device (e.g., themedical device 110 or the medical device 510) may capture the sequenceof image frames of the subject. The one or more cameras may be installedon suitable positions of the medical device in order to capture thesequence of image frames of the subject. In some embodiments, thecaptured image frames may be stored in a storage device (e.g., thestorage device 130 or the storage device 550). The acquisition module602 may acquire the image frames from the storage device.

In 804, the processing device (e.g., the first data determination module604 of the processing device 540) may determine, based on at least apart of the plurality of image frames, first data including one or moremotion parameters.

In some embodiments, the first data may refer to data related to thefirst motion (e.g., the rigid motion). In some embodiments, the firstdata determination module 604 may determine the one or more motionparameters according to the at least a part of the plurality of imageframes. The one or more motion parameters may include athree-dimensional translation matrix and/or a three dimensional rotationmatrix. The rigid motion (i.e., the first motion) may be measured by theone or more motion parameters.

In some embodiments, the one or more motion parameters may be determinedusing a tracking marker. Specifically, the tracking marker may be fixedon the subject or an ROI of the subject during the scan of the medicaldevice. The tracking marker may be represented as a specific imagetexture in an image frame. In some embodiments, the rigid motion of thesubject may be identified by tracking the motion of the tracking markerin at least two of the plurality of image frames. The first datadetermination module 604 may segment the tracking marker and the subject(or the ROI of the subject) from the image frame. The first datadetermination module 604 may obtain coordinates of the tracking markerin different image frames, respectively. The obtained coordinates arethe coordinates in the camera coordinate system (hereinafter cameracoordinates related to the tracking marker). The first datadetermination module 604 may determine the motion parameters based onthe camera coordinates related to the tracking marker in different imageframes.

Assuming that f₀ denotes a first image frame captured at the time pointt₀, f₁ denotes a second image frame captured at the time point t₁.X_(c0) denotes the coordinates related to the tracking marker at t₀, andX_(c1) denotes the coordinates related to the tracking marker at t₁. LetR_(c) be a rotation matrix and T_(c) be a translation matrix for therigid motion of the tracking marker between t₀ and t₁, respectively. Therigid motion may be described by Equation (1) as follows:

X _(c1) =R _(c) X _(c0) +T _(c).  (1)

In some embodiments, X_(c0) and X_(c1) may be a 3×N dimensional matrix,where N denotes the number (or count) of the tracking marker(s). In someembodiments, Equation (2) may be introduced to determine R_(c) andT_(c):

C=[X _(c0)− X _(c0) ][X _(c1)− X _(c1) ],  (2)

where X_(c0) and X_(c1) are mean coordinate matrices of N trackingmarkers, respectively. In some embodiments, the first data determinationmodule 604 may solve Equation (2) using, e.g., singular valuedecomposition (SVD). R_(c) and T_(c) may be determined based on thesolutions of Equation (2). In some embodiments, if R_(c) and T_(c) arezero matrices, then no rigid motion exists between the time points t₀and t₁. In other words, the subject did not move between the time pointst₀ and t₁. In some embodiments, if at least one of R_(c) and T_(c) is anon-zero matrix, there may exist rigid motion between the time points t₀and t₁. In other words, the subject may have moved between the timepoints t₀ and t₁. The rigid motion may be identified based on the motionparameters. In some embodiments, the rigid motion related data (e.g.,the motion parameters) may be fed back to the one or more radars.

In 806, the the processing device (e.g., the acquisition module 602 ofthe processing device 540) may acquire radar echo data from the subject.In some embodiments, the radar echo data and the the plurality of imageframes may be acquired simultaneously by the one or more radars and theone or more cameras, respectively. That is, the operation 802 and theoperation 806 may be performed simultaneously.

In some embodiments, the acquisition module 602 may acquire the radarecho data acquired by the one or more radars in real time. Exemplaryradars may include a continuous wave (CW) radar, an ultra wideband (UWB)radar, or a frequency modulated continuous wave (FMCW) radar, and so on.The one or more radars may be installed at suitable positions on or inthe vicinity of the medical device in order to capture radar echosignals indicative of the physiological motion (i.e., the second motion)of the subject. In some embodiments, the captured radar echo data may bestored in a storage device (e.g., the storage device 130 or the storagedevice 550). The acquisition module 602 may acquire the radar echo datafrom the storage device 130. In some embodiments, the one or more radarsmay detect both the physiological motion and the rigid motion if thereexists the rigid motion during the scan. In this case, if the radar echodata without a correction is used to determine a physiological motionrelated data directly, the determined physiological motion related datamay be inaccurate because the radar echo data includes disturbedinformation caused by the rigid motion.

In 808, the processing device (e.g., the second data determinationmodule 606 of the processing device) may correct the radar echo dataaccording to the one or more motion parameters of the first motion(e.g., the rigid motion).

The determined one or more motion parameters, based on Equation (1) andEquation (2), correspond to the camera coordinate system. To correct theradar echo data, the one or more motion parameters in the cameracoordinate system may be transformed into the radar coordinate system.In some embodiments, system calibration between the camera coordinatesystem and the radar coordinate system may be performed.

Merely by way of example, FIG. 9 illustrates an exemplary systemcalibration between the camera coordinate system and the radarcoordinate systems according to some embodiments of the presentdisclosure. As shown in FIG. 9 , let O_(c)X_(c)Y_(c)Z_(c) be the cameracoordinate system, and let O_(r)X_(r)Y_(r)Z_(r) be the radar coordinatesystem. The system calibration may be described by Equation (3) asfollows:

X _(r) =R _(cr) X _(c) +T _(cr),  (3)

where X_(r) denotes the coordinates in the radar coordinate system,X_(c) denotes the coordinates in the camera coordinate system, R_(cr)denotes the rotation matrix between the camera coordinate system and theradar coordinate system, and T_(cr) denotes the translation matrixbetween the camera coordinate system and the radar coordinate system. Insome embodiments, the second data determination module 606 may determineone or more motion parameters corresponding to the radar coordinatessystem (also referred to as second motion parameters) based on the oneor more motion parameters corresponding to the camera coordinate system(also referred to as first motion parameters). The second motionparameters may include the rotation matrix R_(r) and the translationmatrix T_(r) in the radar coordinate system. In some embodiments,because the second motion parameters and the radar echo data are in thesame coordinate system, the second data determination module 606 maycorrect the radar echo data based on the second motion parameters. Forexample, the second data determined module 606 may determine disturbedinformation corresponding to the second motion paramters, and correctthe radar echo data by filtering out the disturbed information.

Assuming that X_(r0) denotes the coordinates of a tracking marker in theradar coordinate system at t₀, and X₁ denotes the coordinates of thetracking marker in the radar coordinate system at t₁. Thus,

X _(r0) =R _(cr) X _(c0) +T _(cr),  (4) and

X _(r1) =R _(cr) X _(c1) +T _(cr).  (5)

In some embodiments, X_(r1) may be described by combining Equation (1)and Equation (4):

X _(r1) =R _(cr) R _(c) R _(cr) ⁻¹ X _(r0) −R _(cr) R _(c) R _(cr) ⁻¹ T_(cr) +R _(cr) T _(c) +T _(cr) =R _(r) X _(r0) +T _(r).  (6)

In some embodiments, the second data determination module 606 maydetermine the rotation matrix R_(r) and the translation matrix T_(r) inthe radar coordinate system based on Equation (6). For example,

R _(r) =R _(cr) R _(c) R _(cr) ⁻¹, and T _(r) =−R _(cr) R _(c) R _(cr)⁻¹ T _(cr) +R _(cr) T _(c) +T _(cr).  (7)

In 810, the processing device (e.g., the second data determinationmodule 606 of the processing device) may extract, from the correctedradar echo data, the second data including cardiac motion data and/orrespiratory motion data.

In some embodiments, the second data may refer to data related to thesecond motion (e.g., the physiological motion). The second data mayinclude cardiac motion data (e.g., an ECG signal) and respiratory motiondata. Specifically, the second data determination module 606 mayextract, from the corrected radar echo data, the cardiac motion data andthe respiratory motion data, respectively. For example, the second datadetermination module 606 may perform an oblique removal operation forthe corrected radar echo data. The oblique removal operation mayinclude: it mixs an input signal with a reference signal (a localoscillator signal with appropriate delay, the delay is usually estimatedfrom the result of narrowband signal ranging); then each scatteringpoint corresponds to a single frequency component after mixing, and adiscrete fourier transformation (DFT) is performed for themixed-frequency output signal. The second data determination module 606may filter the radar echo data after the oblique removal. The filteredradar echo data may be amplified by an amplifier. The amplified radarecho data may be divided into the cardiac motion data and respiratorymotion data by a signal separator (e.g., a demultiplexer). In someembodiments, the cardiac motion data and the respiratory motion data maybe sent to the medical device for real time controlling the medicaldevice.

Merely by way of example, FIG. 10 illustrates an exemplary respiratorysignal 1000, and FIG. 11 illustrates an exemplary ECG signal. FIG. 10showns a respiratory signal 1000 extracted from the radar echo signalafter the rigid motion correction. The respiratory signal may include arespiratory waveform. The respiratory waveform may include a pluralityof respiratory cycles. FIG. 11 shows an ECG signal extracted from theradar echo data after the rigid motion correction. The ECG signal may beextracted based on the Q channel and I channel of the radar echo signal.Q channel and I channel are two orthogonal channels of the radar.

FIG. 12 is a flowchart illustrating an exemplary process for generatingan image according to some embodiments of the present disclosure.Process 1200 may be implemented in the medical system 100 illustrated inFIG. 1 or the medical imaging system 500 illustrated in FIG. 5 . Forexample, the process 1200 may be stored in the storage device 130 and/orthe storage device 550 in the form of instructions (e.g., anapplication), and invoked and/or executed by the processing device 120(e.g., the processing device 540 illustrated in FIG. 5 , or one or moremodules in the processing device 540 illustrated in FIG. 6 ). Theoperations of the illustrated process presented below are intended to beillustrative. In some embodiments, the process 1200 may be accomplishedwith one or more additional operations not described, and/or without oneor more of the operations discussed. Additionally, the order in whichthe operations of the process 1200 as illustrated in FIG. 12 anddescribed below is not intended to be limiting.

In 1202, the processing device (e.g., the acquisition module 602 of theprocessing device 540) may acquire scan data of a subject through amedical device. For example, during the medical device (e.g., an MRIdevice) scans the subject or at least a part of the subject, theacquisition module 602 may acquire the scan data related to the subjector the at least a part of the subject in real time or near real time.The acquired scan data may be stored in a storage device (e.g., thestorage device 550).

In 1204, the processing device (e.g., the acquisition module 602 of theprocessing device 540) may acquire, via one or more radars, radar echodata from the subject during the scan. The radar echo data may be usedto characterize a physiological motion (i.e., the second motionmentioned above) of the subject. In some embodiments, the one or moreradars may be installed at suitable positions on or in the vicinity ofthe medical device in order to capture radar echo signals indicative ofthe physiological motion of the subject. In some embodiments, the radarecho data may be stored in a storage device (e.g., the storage device550).

In 1206, the processing device (e.g., the acquisition module 602 of theprocessing device 540) may acquire, via one or more cameras, a pluralityof image frames of the subject. The radar echo data may be used tocharacterize a rigid motion (i.e., the first motion mentioned above) ofthe subject. In some embodiments, the one or more cameras may beinstalled at suitable positions on or in the vicinity of the medicaldevice in order to capture the plurality of image frames for identifyingthe rigid motion of the subject. In some embodiments, the plurality ofimage frames may be stored in a storage device (e.g., the storage device550).

In 1208, the processing device (e.g., the reconstruction module 610 ofthe processing device 540) may generate an image based on the scan data,the radar echo data and the plurality of image frames (operation 1008).

In some embodiments, the medical device may acquire the scan dataconticontinuously according to a retrospective gating technique. Thereconstruction module 610 may obtain reconstruction data from the scandata based on the radar echo data and the plurality of image frames.However, in some embodiments, the one or more radars may detect both thephysiological motion (i.e., the second motion) and the rigid motion(i.e., the first motion) if there exists the rigid motion during thescan. In this case, if the radar echo data without a correction is usedto determine physiological motion related data directly, the determinedphysiological motion related data may be inaccurate because the radarecho data includes disturbed information caused by the rigid motion. Toresolve this issue, the radar echo data may be corrected based on theplurality of image frames.

Specifically, the first data determination module 604 of the processingdevice 540 may determine, based on at least a part of the plurality ofimage frames, first data regarding the first motion (i.e., rigid motionrelated data). The first data may include one or more motion paramtersof the rigid motion of the subject. The second data determination module604 of the processing device 540 may correct the radar echo dataaccording to the one or more motion parameters of the rigid motion. Thesecond data determination module 604 may extract, from the correctedradar echo data, second data including cardiac motion data (e.g., theECG signal illustrated in FIG. 11 ) and/or respiratory motion data(e.g., the ECG signal illustrated in FIG. 10 ). More detaileddescriptions of first data and second data may be found elsewhere in thepresent disclosure, see, e.g., FIG. 8 and the descriptions thereof, andnot repeated herein.

In some embodiments, the reconstruction module 610 may obtain thereconstruction data from the scan data based on the cardiac motion dataor the respiratory data. For example, the reconstruction module 610 mayobtain scan data corresponding to one or more specific cardiac cycles.The one or more specific cardiac cycles may be identified based on thecardiac motion data (e.g., the ECG signal). The scan data correspondingto the specific cardiac cycles may be designated as the reconstructiondata. The reconstruction module 610 may reconstruct the image based onthe designated reconstruction data. As another example, thereconstruction module 610 may obtain scan data corresponding to one ormore specific respiratory cycles (e.g., one or more expiration periods).The one or more specific respiratory cycles may be identified based onthe respiratory motion data (e.g., the respiratory signal). The scandata corresponding to the specific respiratory cycles may be designatedas the reconstruction data. The reconstruction module 610 mayreconstruct the image based on the designated reconstruction data. Itshould be understood that the fuse of the radar echo data and the imageframes may be assisted to determine accurate cardiac motion data andrespiratory motion data. The accurate cardiac motion data andrespiratory motion data may facilitate to reduce or avoid motionartifacts (e.g., cardiac motion artifacts or respiratory motionartifacts) in the reconstructed image.

It should be noted that the description of the process 1200 is providedfor the purposes of illustration, and not intended to limit the scope ofthe present disclosure. For persons having ordinary skills in the art,various variations and modifications may be conducted under the teachingof the present disclosure. For example, operations 1202 to 1206 may beintegrated into a single operation, and/or be performed simultaneously.However, those variations and modifications may not depart from theprotecting of the present disclosure.

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by the present disclosure,and are within the spirit and scope of the exemplary embodiments of thepresent disclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and/or “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Accordingly, aspects of the presentdisclosure may be implemented entirely hardware, entirely software(including firmware, resident software, micro-code, etc.) or combiningsoftware and hardware implementation that may all generally be referredto herein as a “unit,” “module,” or “system.” Furthermore, aspects ofthe present disclosure may take the form of a computer program productembodied in one or more computer readable media having computer readableprogram code embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, radiofrequency (RF), or the like, or any suitable combination of theforegoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET,Python or the like, conventional procedural programming languages, suchas the “C” programming language, Visual Basic, Fortran 2103, Perl, COBOL2102, PHP, ABAP, dynamic programming languages such as Python, Ruby andGroovy, or other programming languages. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider) or in a cloud computing environment or offered as aservice such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations, therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose and that the appended claimsare not limited to the disclosed embodiments, but, on the contrary, areintended to surface modifications and equivalent arrangements that arewithin the spirit and scope of the disclosed embodiments. For example,although the implementation of various components described above may beembodied in a hardware device, it may also be implemented as a softwareonly solution, for example, an installation on an existing server ormobile device.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped in a single embodiment, figure, or description thereof for thepurpose of streamlining the disclosure aiding in the understanding ofone or more of the various inventive embodiments. This method ofdisclosure, however, is not to be interpreted as reflecting an intentionthat the claimed subject matter requires more features than areexpressly recited in each claim. Rather, inventive embodiments lie inless than all features of a single foregoing disclosed embodiment.

In some embodiments, the numbers expressing quantities or propertiesused to describe and claim certain embodiments of the application are tobe understood as being modified in some instances by the term “about,”“approximate,” or “substantially.” For example, “about,” “approximate,”or “substantially” may indicate ±20% variation of the value itdescribes, unless otherwise stated. Accordingly, in some embodiments,the numerical parameters set forth in the written description andattached claims are approximations that may vary depending upon thedesired properties sought to be obtained by a particular embodiment. Insome embodiments, the numerical parameters should be construed in lightof the number of reported significant digits and by applying ordinaryrounding techniques. Notwithstanding that the numerical ranges andparameters setting forth the broad scope of some embodiments of theapplication are approximations, the numerical values set forth in thespecific examples are reported as precisely as practicable.

Each of the patents, patent applications, publications of patentapplications, and other material, such as articles, books,specifications, publications, documents, things, and/or the like,referenced herein is hereby incorporated herein by this reference in itsentirety for all purposes, excepting any prosecution file historyassociated with same, any of same that is inconsistent with or inconflict with the present document, or any of same that may have alimiting affect as to the broadest scope of the claims now or laterassociated with the present document. By way of example, should there beany inconsistency or conflict between the description, definition,and/or the use of a term associated with any of the incorporatedmaterial and that associated with the present document, the description,definition, and/or the use of the term in the present document shallprevail.

In closing, it is to be understood that the embodiments of theapplication disclosed herein are illustrative of the principles of theembodiments of the application. Other modifications that may be employedmay be within the scope of the application. Thus, by way of example, butnot of limitation, alternative configurations of the embodiments of theapplication may be utilized in accordance with the teachings herein.Accordingly, embodiments of the present application are not limited tothat precisely as shown and described.

We claim:
 1. A method for image reconstruction implemented on acomputing device having at least one processor and at least one storagedevice, the method comprising: acquiring scan data of a subjectcollected by a medical device in a scan of the subject; acquiring aplurality of image frames regarding a first motion of the subject duringthe scan and radar echo data regarding a second motion of the subjectduring the scan, the plurality of image frames being collected via oneor more cameras, the radar echo data being collected via one or moreradars; generating one or more medical images of the subject based onthe scan data, the plurality of image frames, and the radar echo data.2. The method of claim 1, wherein the first motion includes a rigidmotion of the subject, and the second motion includes a physiologicalmotion of the subject.
 3. The method of claim 1, wherein the generatingone or more medical images of the subject based on the scan data, theplurality of image frames, and the radar echo data comprises: correctingthe radar echo data based on the plurality of image frames; obtainingreconstruction data from the scan data based on the corrected radar echodata; reconstructing the one or more medical images based on thereconstruction data.
 4. The method of claim 3, wherein the correctingthe radar echo data based on the plurality of image frames comprises:determining, based on the plurality of image frames, first dataregarding the first motion, the first data including one or more motionparameters of the first motion; and correcting the radar echo dataaccording to the one or more motion parameters.
 5. The method of claim4, wherein the one or more motion parameters of the first motion includeone or more translation matrices and one or more rotation matrices. 6.The method of claim 3, wherein the obtaining reconstruction data fromthe scan data based on the corrected radar echo data comprises:extracting, from the corrected radar echo data, second data regardingthe second motion, the second data including at least one of cardiacmotion data or respiratory motion data; obtaining the reconstructiondata from the scan data based on the at least one of the cardiac motiondata or the respiratory motion data.
 7. The method of claim 6, whereinthe obtaining the reconstruction data from the scan data based on the atleast one of the cardiac motion data or the respiratory motion datacomprises: designating, based on the cardiac motion data, scan datacorresponding to one or more specific cardiac cycles as thereconstruction data; or designating, based on the respiratory motiondata, scan data corresponding to one or more specific respiratory cyclesas the reconstruction data.
 8. The method of claim 1, wherein theplurality of image frames and the radar echo data are acquiredsimultaneously by the one or more cameras and the one or more radars,respectively.
 9. The method of claim 1, wherein the medical deviceincludes at least one of a computed tomography (CT) device, a magneticresonance imaging (MRI) device, a positron emission tomography (PET)device, or a radiation therapy (RT) device.
 10. A system, comprising: atleast one storage device storing a set of instructions for imagereconstruction; and at least one processor configured to communicatewith the at least one storage device, wherein when executing the set ofinstructions, the at least one processor is configured to direct thesystem to perform operations including: acquiring scan data of a subjectcollected by a medical device in a scan of the subject; acquiring aplurality of image frames regarding a first motion of the subject duringthe scan and radar echo data regarding a second motion of the subjectduring the scan, the plurality of image frames being collected via oneor more cameras, the radar echo data being collected via one or moreradars; generating one or more medical images of the subject based onthe scan data, the plurality of image frames, and the radar echo data.11. The system of claim 10, wherein the first motion includes a rigidmotion of the subject, and the second motion includes a physiologicalmotion of the subject.
 12. The system of claim 10, wherein thegenerating one or more medical images of the subject based on the scandata, the plurality of image frames, and the radar echo data comprises:correcting the radar echo data based on the plurality of image frames;obtaining reconstruction data from the scan data based on the correctedradar echo data; reconstructing the one or more medical images based onthe reconstruction data.
 13. The system of claim 12, wherein thecorrecting the radar echo data based on the plurality of image framescomprises: determining, based on the plurality of image frames, firstdata regarding the first motion, the first data including one or moremotion parameters of the first motion; and correcting the radar echodata according to the one or more motion parameters.
 14. The system ofclaim 13, wherein the one or more motion parameters of the first motioninclude one or more translation matrices and one or more rotationmatrices.
 15. The system of claim 12, wherein the obtainingreconstruction data from the scan data based on the corrected radar echodata comprises: extracting, from the corrected radar echo data, seconddata regarding the second motion, the second data including at least oneof cardiac motion data or respiratory motion data; obtaining thereconstruction data from the scan data based on the at least one of thecardiac motion data or the respiratory motion data.
 16. The system ofclaim 15, wherein the obtaining the reconstruction data from the scandata based on the at least one of the cardiac motion data or therespiratory motion data comprises: designating, based on the cardiacmotion data, scan data corresponding to one or more specific cardiaccycles as the reconstruction data; or designating, based on therespiratory motion data, scan data corresponding to one or more specificrespiratory cycles as the reconstruction data.
 17. The system of claim10, wherein the plurality of image frames and the radar echo data areacquired simultaneously by the one or more cameras and the one or moreradars, respectively.
 18. The system of claim 10, wherein the medicaldevice includes at least one of a computed tomography (CT) device, amagnetic resonance imaging (MRI) device, a positron emission tomography(PET) device, or a radiation therapy (RT) device.
 19. A non-transitorycomputer readable medium, comprising a set of instructions for imagereconstruction, wherein when executed by at least one processor, the setof instructions direct the at least one processor to effectuate amethod, the method comprising: acquiring scan data of a subjectcollected by a medical device in a scan of the subject; acquiring aplurality of image frames regarding a first motion of the subject duringthe scan and radar echo data regarding a second motion of the subjectduring the scan, the plurality of image frames being collected via oneor more cameras, the radar echo data being collected via one or moreradars; generating one or more medical images of the subject based onthe scan data, the plurality of image frames, and the radar echo data.20. The non-transitory computer readable medium of claim 19, wherein thefirst motion includes a rigid motion of the subject, and the secondmotion includes a physiological motion of the subject.